Journal of
Plant Breeding and Crop Science

  • Abbreviation: J. Plant Breed. Crop Sci.
  • Language: English
  • ISSN: 2006-9758
  • DOI: 10.5897/JPBCS
  • Start Year: 2009
  • Published Articles: 447

Full Length Research Paper

Evaluation of soybean (Glycine max (L.) Merr.) breeding lines and genotype-by-environment interaction across production environments in Southern Africa

Christabell Nachilima
  • Christabell Nachilima
  • International Institute of Tropical Agriculture (IITA), Lusaka, Zambia.
  • Google Scholar
Henry Cordoba-Novoa
  • Henry Cordoba-Novoa
  • Department of Plant Science, McGill University, Montreal, Quebec, Canada.
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Valerio Hoyos-Villegas
  • Valerio Hoyos-Villegas
  • Department of Plant Science, McGill University, Montreal, Quebec, Canada.
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Godfree Chigeza
  • Godfree Chigeza
  • International Institute of Tropical Agriculture (IITA), Lusaka, Zambia.
  • Google Scholar
Noah Manda
  • Noah Manda
  • International Institute of Tropical Agriculture (IITA), Lusaka, Zambia.
  • Google Scholar
David Lungu
  • David Lungu
  • Department of Plant Science, University of Zambia, Lusaka, Zambia.
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Kelvin Kamfwa
  • Kelvin Kamfwa
  • Department of Plant Science, University of Zambia, Lusaka, Zambia.
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  •  Received: 29 September 2021
  •  Accepted: 04 November 2021
  •  Published: 31 December 2021

Abstract

Yield is a quantitative trait known to be influenced by changes in the environment in which the crop is grown, suggesting the need to evaluate soybean lines in different growing regions to assess their adaptability and stability. The objective of this study was to evaluate the performance, yield stability, and genotype × environment interaction (G×E) in soybean cultivars, and the informativeness of six environments in Southern Africa. A group of 62 soybean lines was grown and tested in six locations in Malawi and Zambia during the growing seasons in 2018 and 2019 using a 6 x 5 and 5 x 5 alpha lattice design. Genotype plus genotype × environment (GGE) biplots were used to reduce data complexity and analyze genotypes performance and stability; environments discriminativeness and representativeness; and traits associated with yield. The GGE analyses showed a significant effect of genotypes, environments, and G×E. Genotypes with local and wide adaptation and environments with desirable characteristics for testing cultivars were identified. A number of agronomic traits were identified to be positively and negatively associated with soybean yield. These results reinforce the utility of GGE analysis for ranking cultivars and environments in soybean breeding programs in Southern Africa.

Key words: GGE, yield, adaptation, stability, heritability, flowering.

Abbreviation

AMMI, Additive Main effect and Multiplicative Interaction; GGE, Genotype plus genotype by environment; G X E, genotype by environment interaction